A Model-Data-Hybrid-Driven Diagnosis Method for Open-Switch Faults in Power Converters

Li, Zhan; Gao, Yuan; Zhang, Xin; Wang, Borong; Ma, Hao

Abstract

To combine the advantages of both model-driven and data-driven methods, this article proposes a model-data-hybrid-driven method to diagnose open-switch faults in power converters. This idea is based on the explicit analytical model of converters and the learning capability of the artificial neural network (ANN). The process of the method is divided into two parts: offline model analysis and learning, and online fault diagnosis. For both parts, model-driven and data-driven are combined. With the model information and data-based learning capability, a fast diagnosis for various operating conditions can be achieved without a high computation burden, tricky threshold selection, and complex rulemaking. This can greatly contribute to the practical application. The open-switch fault diagnosis in a two-level three-phase converter is studied for the method validation. For this converter, an ANN is trained with two input elements, seven output elements, and two neurons in the hidden layer. Experimental results are given to demonstrate good performance.

Citation

Li, Z., Gao, Y., Zhang, X., Wang, B., & Ma, H. (2020). A Model-Data-Hybrid-Driven Diagnosis Method for Open-Switch Faults in Power Converters. IEEE Transactions on Power Electronics, 36(5), 4965-4970. https://doi.org/10.1109/TPEL.2020.3026176

• Journal Article Type: Article
• Acceptance Date: Sep 8, 2020
• Online Publication Date: Sep 23, 2020
• Publication Date: Sep 23, 2020
• Deposit Date: Sep 28, 2020
• Publicly Available Date: Sep 28, 2020
• Journal: IEEE Transactions on Power Electronics
• Print ISSN: 0885-8993
• Electronic ISSN: 1941-0107
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 36
• Issue: 5
• Pages: 4965-4970
• DOI: https://doi.org/10.1109/TPEL.2020.3026176
• Keywords: Electrical and Electronic Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/4925047
• Publisher URL: https://ieeexplore.ieee.org/document/9204836
• Additional Information: “© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”; ; Li, Z., Gao, Y., Zhang, X., Wang, B., & Ma, H. (2020). A Model-Data-Hybrid-Driven Diagnosis Method for Open-Switch Faults in Power Converters. IEEE Transactions on Power Electronics, 1–1. https://doi.org/10.1109/tpel.2020.3026176